SCHOOL OF COMPUTING, NUS
DOCTORAL SEMINAR BY
MR DONG DIFENG
Computational techniques for drug pathway identification and
disease treatment optimization
Meeting Room 4(COM1 01-23)
24 January 2008, 1.30pm
Abstract:
Gene expression analysis techniques have been used for disease
subtype diagnosis, disease subtype discovery, and treatment response
understanding in the last decade. The research crux now is how to
interpret a list of identified genes in biological context; or in
other words, how to select genes with respect to biological meaning.
Biological pathways contain potential information to answer these
questions. Since gene products function by interacting with each
other, pathways provide a benchmark for cancer researchers to
select, rank, and evaluate genes against high-throughput expression
datasets. In our current research, we design computational systems
to understand drug treatment response in biological pathway context.
Our target is to evaluate drug effect for individual organisms and
provide directions for cancer treatment optimization.
In this proposal, we introduce the background of our research,
summarizing the achievements in disease subtype diagnosis, new
subtype discovery, and treatment response understanding, with an
in-depth review of expression analysis with biological networks.
Recently, we have designed a drug pathway identification system for
a nasopharyngeal carcinoma (NPC) study. In this study, 3 NPC cell
lines and 13 NPC patients were treated with a cyclin dependent
kinase (CDK) inhibitor, CYC202. As a result of the treatment, both
cell lines and patients responded to the treatment differentially.
Our system generates hypotheses for the regulated genetic pathways
in response to the drug treatment, and identify the differentiation
of pathway status between individuals. Interestingly, the evaluated
pathway status are consistent between the two experiment groups, and
perfectly separating the responders and non-responders in the
patient dataset. Furthermore, we confirm our discovery with extra
medical assays and publications in literature. Both results suggest
the identifications of our system provides plausible hypotheses for
further research.